Prediction of the Endocrine disruption profile of fluorinated biphenyls and analogues: An in silico study

Using machine learning to classify the immunosuppressive activity of per- and polyfluoroalkyl substances

Per- and polyfluoroalkyl substances (PFASs), one of the persistent organic pollutants, have immunosuppressive effects. The evaluation of this effect has been the focus of regulatory toxicology. In this investigation, 146 PFASs (immunosuppressive or nonimmunosuppressive) and corresponding concentration gradients were collected from literature, and their structures were characterized by using Dragon descriptors. Feature importance analysis and stepwise feature elimination are used for feature selection. Three machine learning (ML) methods, namely Random Forest (RF), Extreme Gradient Boosting Machine (XGB), and Categorical Boosting Machine (CB), were utilized for model development. The model interpretability was explored by feature importance analysis and correlation analysis. The findings indicated that the three models developed have exhibited excellent performance. Among them, the best-performing RF model has an average AUC score of 0.9720 for the testing set. The results of the feature importance analysis demonstrated that concentration, SpPosA_X, IVDE, R2s, and SIC2 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. In conclusion, this study is the first application of ML models to investigate the immunosuppressive activity of PFASs. The variables used in the models can help understand the mechanism of the immunosuppressive activity of PFASs, allow researchers to more effectively assess the immunosuppressive potential of a large number of PFASs, and thus better guide environmental and health risk assessment efforts.

Fluorinated liquid-crystal monomers in infant formulas and implication for health risk

Fluorinated liquid-crystal monomers (FLCMs), a new class of potential persistent, bioaccumulative and toxic (PBT) emerging pollutants, are extensively utilized in the display panel of various electronic devices. These compounds have been found in various environmental matrixes and dietary. Our previous studies have documented their ubiquitous occurrence in high fat foodstuffs. Infants, a vulnerable group, are more susceptible to the impacts of these pollutants compared to adults. Herein, we provided an assessment of the health risks posed by FLCMs to infants, focusing on their exposure through infant formula. The presence of FLCMs was detected in all infant formulas, with median concentration of 16.5 ng/g dry weight (dw) and the 95th percentile concentration of 65.7 ng/g dw. The most prevalent pollutant in these formulas was 2-fluoro-4-[4'-propyl-1,1'-bi(cyclohexyl)-4-yl] phenyl trifluoromethyl ether (FPrBP), with median and a 95th percentile concentration of 12.2 ng/g dw and 23.8 ng/g dw, accounting for 55.2% to the total FLCMs. Infants aged 0-6 months had the highest estimated daily intakes (EDIs) of FLCMs, with the EDImedian of 267 ng/kg bw/day. FPrBP and 4-[trans-4-(trans-4-Propylcyclohexyl) cyclohexyl]-1-trifluoromethoxybenzene (PCTB) together made up 83.3% of the total EDIs in median exposure scenario of 0-6 months infant. The highest EDI value was 1.30 × 103 ng/kg bw/day, 77.1% of which was attributed to a combination of FPrBP, 4″-ethyl-2'-fluoro-4-propyl-1,1':4',1″-terphenyl (EFPT), 2-[4'-[difluoro(3,4,5-trifluoro-2-methyl-phenoxy)methyl]-3',5'-difluoro-[1,1'-biphenyl]-4-yl]-5-ethyl-tetrahydro-pyran (DTMPMDP), 4-[Difluoro-(3,4,5-trifluoro-2-methyl-phenoxy)-methyl]-3,5-difluoro-4'-propyl-1,1-biphenyl (DTMPMDB), 2,3-difluoro-1-methyl-4-[(trans, trans)-4'-pentyl[1,1'-bicyclohexyl]-4-yl]benzene (DMPBB) and PCTB. It's worth noting that FLCMs have higher exposure risk. Based on the threshold of toxicological concern (TTC) method, the EDImedian of FPrBP (183 ng/kg bw/day) and FPCB (3.27 ng/kg bw/day) were beyond their TTC values (2.5 ng/kg bw/day) in 0-6 months infant, implying their prospective health risk.

Characteristic structures of liquid crystal monomers in EI-MS analysis and the potential application in suspect screening

Liquid crystal monomers (LCMs) are of emerging concern due to their ubiquitous presence in indoor and outdoor environments and their potential negative impacts on human health and ecosystems. Suspect screening approaches have been developed to monitor thousands of LCMs that could enter the environment, but an updated suspect list of LCMs is difficult to maintain given the rapid development of material innovations. To facilitate suspect screening for LCMs, in-silico mass fragmentation model and quantitative structure-activity relationship (QSPR) models were applied to predict electron ionization (EI) mass spectra of LCMs. The in-silico model showed limited predictive power for EI mass spectra, while the QSPR models trained with 437 published mass spectra of LCMs achieved an acceptable absolute error of 12 percentage points in predicting the relative intensity of the molecular ion, but failed to predict the mass-to-charge ratio of the base peak. A total of 41 characteristic structures were identified from an updated suspect list of 1606 LCMs. Multi-phenyl groups form the rigid cores of 85% of LCMs and produce 154 characteristic peaks in EI mass spectra. Monitoring the characteristic structures and fragments of LCMs may help identify new LCMs with the same rigid cores as those in the suspect list.

Liquid crystal monomers disrupt photoreceptor patterning of zebrafish larvae via thyroid hormone signaling

Liquid crystal monomers (LCMs) are the raw material for liquid crystal displays, and their use is steadily increasing in electronic products. Recently, LCMs have been reported to be novel endocrine disrupting chemicals, however, the mechanisms underlying their potential for thyroid hormone disruption and visual toxicity are not well understood. In this study, six widely used fluorinated LCMs (FLCMs) were selected to determine putative mechanisms underlying FLCM-induced toxicity to the zebrafish thyroid and visual systems. Exposure to FLCMs caused damage to retinal structures and reduced cell density of ganglion cell layer, inner nuclear layer, and photoreceptor layer approximately 12.6-46.1%. Exposure to FLCMs also disrupted thyroid hormone levels and perturbed the hypothalamic-pituitary-thyroid axis by affecting key enzymes and protein in zebrafish larvae. A thyroid hormone-dependent GH3 cell viability assay supported the hypothesis that FLCMs act as thyroid hormone disrupting chemicals. It was also determined that FLCMs containing aliphatic ring structures may have a higher potential for T3 antagonism compared to FLCMs without an aliphatic ring. Molecular docking in silico suggested that FLCMs may affect biological functions of thyroxine binding globulin, membrane receptor integrin, and thyroid receptor beta. Lastly, the visual motor response of zebrafish in red- and green-light was significantly inhibited following exposure to FLCMs. Taken together, we demonstrate that FLCMs can act as thyroid hormone disruptors to induce visual dysfunction in zebrafish via several molecular mechanisms.

HNF4A as a potential target of PFOA and PFOS leading to hepatic steatosis: Integrated molecular docking, molecular dynamic and transcriptomic analyses

Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are indeed among the most well known and extensively studied Per- and polyfluoroalkyl substances (PFASs), and increasing evidence confirm their effects on human health, especially liver steatosis. Nonetheless, the molecular mechanisms of their initiation of hepatic steatosis is still elusive. Therefore, potential targets of PFOA/PFOS must be explored to ameliorate its adverse consequences. This research aims to investigate the molecular mechanisms of PFOA and PFOS-induced liver steatosis, with emphasis on identifying a potential target that links these PFASs to liver steatosis. The potential target that causes PFOA and PFOS-induced liver steatosis have been explored and determined based on molecular docking, molecular dynamics (MD) simulation, and transcriptomics analysis. In silico results show that PFOA/PFOS can form a stable binding conformation with HNF4A, and PFOA/PFOS may interact with HNF4A to affect the downstream conduction mechanism. Transcriptome data from PFOA/PFOS-induced human stem cell spheres showed that HNF4A was inhibited, suggesting that PFOA/PFOS may constrain its function. PFOS mainly down-regulated genes related to cholesterol synthesis while PFOA mainly up-regulated genes related to fatty acid β-oxidation. This study explored the toxicological mechanism of liver steatosis caused by PFOA/PFOS. These compounds might inhibit and down-regulate HNF4A, which is the molecular initiation events (MIE) that induces liver steatosis.

Aquatic toxicity, ecological effects, human exposure pathways and health risk assessment of liquid crystal monomers

Liquid crystal monomers (LCMs), one of the key materials for liquid crystal displays, have been considered as emerging pollutants in recent years. However, the environmental behaviors of LCMs have not yet been well investigated. The toxicity data of 1173 LCMs were calculated by integrated computational simulation methods in this study. It showed that 64.6% LCMs exhibited PBT (persistent, bioaccumulative, and toxic) properties. Based on the results, 1173 LCMs were identified as molecules possessing the highest level of acute toxicity to aquatic organisms. Among which, and a human health risk priority control list about LCMs was generated in this study, among which 435 were classified as requiring priority control LCMs. It was confirmed that LCMs could eventually accumulate in the human body along the aquatic food chain or penetrate the bloodstream through the dermis, thereby causing harm to health by identifying the exposure pathways of LCMs in humans. Additionally, the electronegativity of the side chain group of LCMs is the main factor causing toxicity differences; therefore, the LCMs containing halogens presented significant acute and chronic toxic effects. This study provided a more comprehensive understanding of LCMs for the public and scientific strategies for controlling LCMs.

Priority list of potential endocrine-disrupting chemicals in food chemical contaminants: a docking study and in vitro/epidemiological evidence integration

Diet is an important exposure route of endocrine-disrupting chemicals (EDCs), but many unfiltered potential EDCs remain in food. The in silico prediction of EDCs is a popular method for preliminary screening. Potential EDCs in food were screened using Endocrine Disruptome, an open-source platform for inverse docking, to predict the binding probabilities of 587 food chemical contaminants with 18 human nuclear hormone receptor (NHR) conformations. In total, 25 contaminants were bound to multiple NHRs such as oestrogen receptor α/β and androgen receptor. These 25 compounds mainly include pesticides and per- and polyfluoroalkyl substances (PFASs). The prediction results were validated with the in vitro data. The structural features and the crucial amino acid residues of the four NHRs were also validated based on previous literature. The findings indicate that the screening has good prediction efficiency. In addition, the epidemic evidence about endocrine interference of PFASs in food on children was further validated through this screening. This study provides preliminary screening results for EDCs in food and a priority list for in vitro and in vivo research.